Overview

Dataset statistics

Number of variables14
Number of observations4328
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory507.2 KiB
Average record size in memory120.0 B

Variable types

Numeric14

Alerts

monetary is highly overall correlated with unique_prods and 6 other fieldsHigh correlation
unique_prods is highly overall correlated with monetary and 4 other fieldsHigh correlation
qt_prods is highly overall correlated with monetary and 7 other fieldsHigh correlation
avg_basket_size is highly overall correlated with unique_prods and 1 other fieldsHigh correlation
recency is highly overall correlated with qt_prods and 2 other fieldsHigh correlation
relationship_duration is highly overall correlated with monetary and 6 other fieldsHigh correlation
purchase_count is highly overall correlated with monetary and 6 other fieldsHigh correlation
returns_count is highly overall correlated with return_rateHigh correlation
return_rate is highly overall correlated with returns_countHigh correlation
avg_purchase_interval is highly overall correlated with monetary and 4 other fieldsHigh correlation
frequency is highly overall correlated with monetary and 4 other fieldsHigh correlation
avg_order_value is highly overall correlated with monetaryHigh correlation
monetary is highly skewed (γ1 = 21.5227491)Skewed
returns_count is highly skewed (γ1 = 26.4818313)Skewed
avg_unit_price is highly skewed (γ1 = 36.53614951)Skewed
return_rate is highly skewed (γ1 = 40.70929296)Skewed
avg_purchase_interval is highly skewed (γ1 = 59.06472112)Skewed
frequency is highly skewed (γ1 = 59.06472112)Skewed
customer_id has unique valuesUnique
relationship_duration has 1555 (35.9%) zerosZeros
returns_count has 2825 (65.3%) zerosZeros
return_rate has 2825 (65.3%) zerosZeros
avg_purchase_interval has 1555 (35.9%) zerosZeros
frequency has 1555 (35.9%) zerosZeros

Reproduction

Analysis started2023-06-25 22:51:24.227513
Analysis finished2023-06-25 22:51:52.339963
Duration28.11 seconds
Software versionydata-profiling vv4.2.0
Download configurationconfig.json

Variables

customer_id
Real number (ℝ)

Distinct4328
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean15301.107
Minimum12347
Maximum18287
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size67.6 KiB
2023-06-25T19:51:52.415255image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum12347
5-th percentile12616.35
Q113813.75
median15299.5
Q316780.25
95-th percentile17984.65
Maximum18287
Range5940
Interquartile range (IQR)2966.5

Descriptive statistics

Standard deviation1721.3706
Coefficient of variation (CV)0.11249975
Kurtosis-1.1957468
Mean15301.107
Median Absolute Deviation (MAD)1484
Skewness0.0019049645
Sum66223189
Variance2963116.8
MonotonicityStrictly increasing
2023-06-25T19:51:52.560985image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
12347 1
 
< 0.1%
16297 1
 
< 0.1%
16272 1
 
< 0.1%
16274 1
 
< 0.1%
16275 1
 
< 0.1%
16276 1
 
< 0.1%
16278 1
 
< 0.1%
16279 1
 
< 0.1%
16281 1
 
< 0.1%
16282 1
 
< 0.1%
Other values (4318) 4318
99.8%
ValueCountFrequency (%)
12347 1
< 0.1%
12348 1
< 0.1%
12349 1
< 0.1%
12350 1
< 0.1%
12352 1
< 0.1%
12353 1
< 0.1%
12354 1
< 0.1%
12355 1
< 0.1%
12356 1
< 0.1%
12357 1
< 0.1%
ValueCountFrequency (%)
18287 1
< 0.1%
18283 1
< 0.1%
18282 1
< 0.1%
18281 1
< 0.1%
18280 1
< 0.1%
18278 1
< 0.1%
18277 1
< 0.1%
18276 1
< 0.1%
18274 1
< 0.1%
18273 1
< 0.1%

monetary
Real number (ℝ)

HIGH CORRELATION  SKEWED 

Distinct4245
Distinct (%)98.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1916.1357
Minimum-796.86
Maximum278778.02
Zeros9
Zeros (%)0.2%
Negative3
Negative (%)0.1%
Memory size67.6 KiB
2023-06-25T19:51:52.720749image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum-796.86
5-th percentile109.0325
Q1298.92
median652.81
Q31610.2275
95-th percentile5650.59
Maximum278778.02
Range279574.88
Interquartile range (IQR)1311.3075

Descriptive statistics

Standard deviation8313.9946
Coefficient of variation (CV)4.3389382
Kurtosis596.66174
Mean1916.1357
Median Absolute Deviation (MAD)453.98
Skewness21.522749
Sum8293035.5
Variance69122507
MonotonicityNot monotonic
2023-06-25T19:51:52.873733image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 9
 
0.2%
76.32 4
 
0.1%
440 3
 
0.1%
113.5 3
 
0.1%
15 3
 
0.1%
363.65 3
 
0.1%
35.4 3
 
0.1%
238.85 2
 
< 0.1%
326.4 2
 
< 0.1%
204 2
 
< 0.1%
Other values (4235) 4294
99.2%
ValueCountFrequency (%)
-796.86 1
 
< 0.1%
-141.48 1
 
< 0.1%
-95.93 1
 
< 0.1%
0 9
0.2%
5.684341886 × 10-141
 
< 0.1%
4.547473509 × 10-131
 
< 0.1%
3.75 1
 
< 0.1%
5.9 1
 
< 0.1%
12.24 1
 
< 0.1%
12.75 1
 
< 0.1%
ValueCountFrequency (%)
278778.02 1
< 0.1%
259657.3 1
< 0.1%
189735.53 1
< 0.1%
133007.13 1
< 0.1%
123638.18 1
< 0.1%
114505.32 1
< 0.1%
88138.2 1
< 0.1%
65920.12 1
< 0.1%
62924.1 1
< 0.1%
59419.34 1
< 0.1%

unique_prods
Real number (ℝ)

Distinct341
Distinct (%)7.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean61.456331
Minimum1
Maximum1786
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size67.6 KiB
2023-06-25T19:51:53.033346image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile4
Q116
median35
Q377
95-th percentile204
Maximum1786
Range1785
Interquartile range (IQR)61

Descriptive statistics

Standard deviation85.364548
Coefficient of variation (CV)1.3890277
Kurtosis99.651934
Mean61.456331
Median Absolute Deviation (MAD)24
Skewness6.917132
Sum265983
Variance7287.106
MonotonicityNot monotonic
2023-06-25T19:51:53.209231image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 93
 
2.1%
10 86
 
2.0%
8 80
 
1.8%
9 79
 
1.8%
11 78
 
1.8%
13 76
 
1.8%
5 73
 
1.7%
15 73
 
1.7%
6 73
 
1.7%
14 72
 
1.7%
Other values (331) 3545
81.9%
ValueCountFrequency (%)
1 93
2.1%
2 52
1.2%
3 60
1.4%
4 52
1.2%
5 73
1.7%
6 73
1.7%
7 72
1.7%
8 80
1.8%
9 79
1.8%
10 86
2.0%
ValueCountFrequency (%)
1786 1
< 0.1%
1766 1
< 0.1%
1322 1
< 0.1%
1118 1
< 0.1%
884 1
< 0.1%
817 1
< 0.1%
717 1
< 0.1%
714 1
< 0.1%
699 1
< 0.1%
636 1
< 0.1%

qt_prods
Real number (ℝ)

Distinct468
Distinct (%)10.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean91.537893
Minimum1
Maximum7838
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size67.6 KiB
2023-06-25T19:51:53.369869image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile4
Q117
median41
Q3100
95-th percentile314.65
Maximum7838
Range7837
Interquartile range (IQR)83

Descriptive statistics

Standard deviation228.63639
Coefficient of variation (CV)2.4977239
Kurtosis483.13585
Mean91.537893
Median Absolute Deviation (MAD)30
Skewness18.102096
Sum396176
Variance52274.597
MonotonicityNot monotonic
2023-06-25T19:51:53.535232image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
10 86
 
2.0%
6 78
 
1.8%
9 75
 
1.7%
1 72
 
1.7%
11 70
 
1.6%
15 70
 
1.6%
8 67
 
1.5%
5 67
 
1.5%
7 66
 
1.5%
28 65
 
1.5%
Other values (458) 3612
83.5%
ValueCountFrequency (%)
1 72
1.7%
2 51
1.2%
3 56
1.3%
4 48
1.1%
5 67
1.5%
6 78
1.8%
7 66
1.5%
8 67
1.5%
9 75
1.7%
10 86
2.0%
ValueCountFrequency (%)
7838 1
< 0.1%
5673 1
< 0.1%
5095 1
< 0.1%
4580 1
< 0.1%
2698 1
< 0.1%
2379 1
< 0.1%
2060 1
< 0.1%
1818 1
< 0.1%
1673 1
< 0.1%
1637 1
< 0.1%

avg_basket_size
Real number (ℝ)

Distinct1029
Distinct (%)23.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean22.291473
Minimum1
Maximum299.70588
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size67.6 KiB
2023-06-25T19:51:53.702847image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2.8633929
Q19.4214286
median17
Q328.4
95-th percentile59.666667
Maximum299.70588
Range298.70588
Interquartile range (IQR)18.978571

Descriptive statistics

Standard deviation20.660891
Coefficient of variation (CV)0.92685175
Kurtosis21.194047
Mean22.291473
Median Absolute Deviation (MAD)8.6666667
Skewness3.2234831
Sum96477.495
Variance426.87241
MonotonicityNot monotonic
2023-06-25T19:51:53.860185image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 99
 
2.3%
13 93
 
2.1%
10 88
 
2.0%
9 82
 
1.9%
11 78
 
1.8%
14 77
 
1.8%
6 74
 
1.7%
7 72
 
1.7%
5 70
 
1.6%
8 69
 
1.6%
Other values (1019) 3526
81.5%
ValueCountFrequency (%)
1 99
2.3%
1.2 1
 
< 0.1%
1.25 1
 
< 0.1%
1.333333333 2
 
< 0.1%
1.5 7
 
0.2%
1.568181818 1
 
< 0.1%
1.571428571 1
 
< 0.1%
1.666666667 4
 
0.1%
1.833333333 1
 
< 0.1%
2 62
1.4%
ValueCountFrequency (%)
299.7058824 1
< 0.1%
259 1
< 0.1%
219 1
< 0.1%
203.5 1
< 0.1%
191 1
< 0.1%
171 1
< 0.1%
164 1
< 0.1%
157 2
< 0.1%
153 1
< 0.1%
148 1
< 0.1%

recency
Real number (ℝ)

Distinct304
Distinct (%)7.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean92.152957
Minimum0
Maximum373
Zeros34
Zeros (%)0.8%
Negative0
Negative (%)0.0%
Memory size67.6 KiB
2023-06-25T19:51:54.020799image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile2
Q117
median50
Q3142
95-th percentile311
Maximum373
Range373
Interquartile range (IQR)125

Descriptive statistics

Standard deviation100.20037
Coefficient of variation (CV)1.0873266
Kurtosis0.42457035
Mean92.152957
Median Absolute Deviation (MAD)40
Skewness1.245256
Sum398838
Variance10040.113
MonotonicityNot monotonic
2023-06-25T19:51:54.177502image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 103
 
2.4%
3 94
 
2.2%
4 94
 
2.2%
2 90
 
2.1%
8 79
 
1.8%
10 77
 
1.8%
17 74
 
1.7%
7 72
 
1.7%
9 70
 
1.6%
22 64
 
1.5%
Other values (294) 3511
81.1%
ValueCountFrequency (%)
0 34
 
0.8%
1 103
2.4%
2 90
2.1%
3 94
2.2%
4 94
2.2%
5 48
1.1%
7 72
1.7%
8 79
1.8%
9 70
1.6%
10 77
1.8%
ValueCountFrequency (%)
373 17
0.4%
372 18
0.4%
371 6
 
0.1%
369 3
 
0.1%
368 5
 
0.1%
367 5
 
0.1%
366 10
0.2%
365 10
0.2%
364 6
 
0.1%
362 6
 
0.1%

relationship_duration
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct374
Distinct (%)8.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean130.73082
Minimum0
Maximum373
Zeros1555
Zeros (%)35.9%
Negative0
Negative (%)0.0%
Memory size67.6 KiB
2023-06-25T19:51:54.336651image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median93
Q3252
95-th percentile357
Maximum373
Range373
Interquartile range (IQR)252

Descriptive statistics

Standard deviation132.31843
Coefficient of variation (CV)1.0121441
Kurtosis-1.3313579
Mean130.73082
Median Absolute Deviation (MAD)93
Skewness0.4528219
Sum565803
Variance17508.168
MonotonicityNot monotonic
2023-06-25T19:51:54.485584image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 1555
35.9%
364 28
 
0.6%
350 26
 
0.6%
357 25
 
0.6%
366 20
 
0.5%
351 20
 
0.5%
355 19
 
0.4%
365 18
 
0.4%
343 18
 
0.4%
356 17
 
0.4%
Other values (364) 2582
59.7%
ValueCountFrequency (%)
0 1555
35.9%
1 9
 
0.2%
2 4
 
0.1%
3 5
 
0.1%
4 4
 
0.1%
5 3
 
0.1%
6 2
 
< 0.1%
7 7
 
0.2%
8 5
 
0.1%
9 3
 
0.1%
ValueCountFrequency (%)
373 5
 
0.1%
372 8
 
0.2%
371 8
 
0.2%
370 8
 
0.2%
369 6
 
0.1%
368 10
 
0.2%
367 11
 
0.3%
366 20
0.5%
365 18
0.4%
364 28
0.6%

purchase_count
Real number (ℝ)

Distinct56
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.2518484
Minimum1
Maximum206
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size67.6 KiB
2023-06-25T19:51:54.647426image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median2
Q35
95-th percentile13
Maximum206
Range205
Interquartile range (IQR)4

Descriptive statistics

Standard deviation7.6516406
Coefficient of variation (CV)1.7996033
Kurtosis244.52051
Mean4.2518484
Median Absolute Deviation (MAD)1
Skewness11.961503
Sum18402
Variance58.547605
MonotonicityNot monotonic
2023-06-25T19:51:54.833975image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1504
34.8%
2 825
19.1%
3 503
 
11.6%
4 394
 
9.1%
5 237
 
5.5%
6 173
 
4.0%
7 138
 
3.2%
8 98
 
2.3%
9 69
 
1.6%
10 55
 
1.3%
Other values (46) 332
 
7.7%
ValueCountFrequency (%)
1 1504
34.8%
2 825
19.1%
3 503
 
11.6%
4 394
 
9.1%
5 237
 
5.5%
6 173
 
4.0%
7 138
 
3.2%
8 98
 
2.3%
9 69
 
1.6%
10 55
 
1.3%
ValueCountFrequency (%)
206 1
< 0.1%
199 1
< 0.1%
124 1
< 0.1%
97 1
< 0.1%
91 2
< 0.1%
86 1
< 0.1%
72 1
< 0.1%
62 2
< 0.1%
60 1
< 0.1%
57 1
< 0.1%

returns_count
Real number (ℝ)

HIGH CORRELATION  SKEWED  ZEROS 

Distinct213
Distinct (%)4.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean23.996765
Minimum0
Maximum9014
Zeros2825
Zeros (%)65.3%
Negative0
Negative (%)0.0%
Memory size67.6 KiB
2023-06-25T19:51:54.986517image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q33
95-th percentile58.65
Maximum9014
Range9014
Interquartile range (IQR)3

Descriptive statistics

Standard deviation234.78991
Coefficient of variation (CV)9.7842316
Kurtosis866.92703
Mean23.996765
Median Absolute Deviation (MAD)0
Skewness26.481831
Sum103858
Variance55126.301
MonotonicityNot monotonic
2023-06-25T19:51:55.126726image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 2825
65.3%
1 169
 
3.9%
2 150
 
3.5%
3 105
 
2.4%
4 89
 
2.1%
6 78
 
1.8%
5 61
 
1.4%
12 52
 
1.2%
7 44
 
1.0%
8 43
 
1.0%
Other values (203) 712
 
16.5%
ValueCountFrequency (%)
0 2825
65.3%
1 169
 
3.9%
2 150
 
3.5%
3 105
 
2.4%
4 89
 
2.1%
5 61
 
1.4%
6 78
 
1.8%
7 44
 
1.0%
8 43
 
1.0%
9 41
 
0.9%
ValueCountFrequency (%)
9014 1
< 0.1%
8004 1
< 0.1%
4427 1
< 0.1%
3768 1
< 0.1%
3332 1
< 0.1%
2878 1
< 0.1%
2022 1
< 0.1%
2012 1
< 0.1%
1776 1
< 0.1%
1594 1
< 0.1%

avg_unit_price
Real number (ℝ)

Distinct4176
Distinct (%)96.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.4664777
Minimum0.1225
Maximum434.65
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size67.6 KiB
2023-06-25T19:51:55.274300image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0.1225
5-th percentile1.3180392
Q12.155125
median2.8285824
Q33.7120688
95-th percentile5.984999
Maximum434.65
Range434.5275
Interquartile range (IQR)1.5569438

Descriptive statistics

Standard deviation8.8708451
Coefficient of variation (CV)2.5590371
Kurtosis1579.0521
Mean3.4664777
Median Absolute Deviation (MAD)0.74715195
Skewness36.53615
Sum15002.916
Variance78.691892
MonotonicityNot monotonic
2023-06-25T19:51:55.415220image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1.06 10
 
0.2%
1.79 8
 
0.2%
2.08 7
 
0.2%
4.95 7
 
0.2%
1.25 7
 
0.2%
2.95 6
 
0.1%
2.55 6
 
0.1%
12.75 5
 
0.1%
4.25 4
 
0.1%
0.72 4
 
0.1%
Other values (4166) 4264
98.5%
ValueCountFrequency (%)
0.1225 1
< 0.1%
0.17 2
< 0.1%
0.2327777778 1
< 0.1%
0.29 2
< 0.1%
0.32 1
< 0.1%
0.358 1
< 0.1%
0.3666666667 1
< 0.1%
0.39 1
< 0.1%
0.3917241379 1
< 0.1%
0.39375 1
< 0.1%
ValueCountFrequency (%)
434.65 1
< 0.1%
295 1
< 0.1%
125 1
< 0.1%
110 2
< 0.1%
74.975 1
< 0.1%
66.475 1
< 0.1%
59.73333333 1
< 0.1%
54.3 1
< 0.1%
51.71 1
< 0.1%
32.97142857 1
< 0.1%

return_rate
Real number (ℝ)

HIGH CORRELATION  SKEWED  ZEROS 

Distinct471
Distinct (%)10.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.6878971
Minimum0
Maximum3004.6667
Zeros2825
Zeros (%)65.3%
Negative0
Negative (%)0.0%
Memory size67.6 KiB
2023-06-25T19:51:55.645702image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile11.2
Maximum3004.6667
Range3004.6667
Interquartile range (IQR)1

Descriptive statistics

Standard deviation55.660421
Coefficient of variation (CV)11.873217
Kurtosis2032.7264
Mean4.6878971
Median Absolute Deviation (MAD)0
Skewness40.709293
Sum20289.219
Variance3098.0825
MonotonicityNot monotonic
2023-06-25T19:51:55.896730image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 2825
65.3%
1 112
 
2.6%
2 81
 
1.9%
0.5 64
 
1.5%
3 52
 
1.2%
0.3333333333 43
 
1.0%
4 40
 
0.9%
1.5 33
 
0.8%
6 32
 
0.7%
0.25 29
 
0.7%
Other values (461) 1017
 
23.5%
ValueCountFrequency (%)
0 2825
65.3%
0.03571428571 1
 
< 0.1%
0.04761904762 1
 
< 0.1%
0.05 1
 
< 0.1%
0.05555555556 1
 
< 0.1%
0.07272727273 1
 
< 0.1%
0.07692307692 1
 
< 0.1%
0.08333333333 1
 
< 0.1%
0.09090909091 2
 
< 0.1%
0.1 6
 
0.1%
ValueCountFrequency (%)
3004.666667 1
< 0.1%
1228 1
< 0.1%
1006 1
< 0.1%
510 1
< 0.1%
426 1
< 0.1%
378.75 1
< 0.1%
336 1
< 0.1%
314 1
< 0.1%
312 1
< 0.1%
300 1
< 0.1%

avg_purchase_interval
Real number (ℝ)

HIGH CORRELATION  SKEWED  ZEROS 

Distinct1229
Distinct (%)28.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.03962258
Minimum0
Maximum34
Zeros1555
Zeros (%)35.9%
Negative0
Negative (%)0.0%
Memory size67.6 KiB
2023-06-25T19:51:56.081891image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0.014925373
Q30.03030303
95-th percentile0.089146825
Maximum34
Range34
Interquartile range (IQR)0.03030303

Descriptive statistics

Standard deviation0.53673128
Coefficient of variation (CV)13.546096
Kurtosis3710.6697
Mean0.03962258
Median Absolute Deviation (MAD)0.014925373
Skewness59.064721
Sum171.48653
Variance0.28808046
MonotonicityNot monotonic
2023-06-25T19:51:56.246861image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 1555
35.9%
0.07142857143 16
 
0.4%
0.04761904762 15
 
0.3%
0.02857142857 14
 
0.3%
0.0303030303 14
 
0.3%
0.01587301587 14
 
0.3%
0.06451612903 13
 
0.3%
0.02380952381 13
 
0.3%
0.1428571429 13
 
0.3%
0.025 12
 
0.3%
Other values (1219) 2649
61.2%
ValueCountFrequency (%)
0 1555
35.9%
0.005464480874 1
 
< 0.1%
0.005479452055 1
 
< 0.1%
0.005494505495 1
 
< 0.1%
0.005509641873 1
 
< 0.1%
0.005602240896 2
 
< 0.1%
0.005617977528 1
 
< 0.1%
0.005633802817 2
 
< 0.1%
0.005681818182 1
 
< 0.1%
0.005698005698 2
 
< 0.1%
ValueCountFrequency (%)
34 1
 
< 0.1%
6 1
 
< 0.1%
4 1
 
< 0.1%
2 6
0.1%
1.5 1
 
< 0.1%
1.333333333 2
 
< 0.1%
1 4
0.1%
0.6666666667 3
0.1%
0.5522788204 1
 
< 0.1%
0.5349462366 1
 
< 0.1%

frequency
Real number (ℝ)

HIGH CORRELATION  SKEWED  ZEROS 

Distinct1229
Distinct (%)28.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.03962258
Minimum0
Maximum34
Zeros1555
Zeros (%)35.9%
Negative0
Negative (%)0.0%
Memory size67.6 KiB
2023-06-25T19:51:56.412071image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0.014925373
Q30.03030303
95-th percentile0.089146825
Maximum34
Range34
Interquartile range (IQR)0.03030303

Descriptive statistics

Standard deviation0.53673128
Coefficient of variation (CV)13.546096
Kurtosis3710.6697
Mean0.03962258
Median Absolute Deviation (MAD)0.014925373
Skewness59.064721
Sum171.48653
Variance0.28808046
MonotonicityNot monotonic
2023-06-25T19:51:56.569794image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 1555
35.9%
0.07142857143 16
 
0.4%
0.04761904762 15
 
0.3%
0.02857142857 14
 
0.3%
0.0303030303 14
 
0.3%
0.01587301587 14
 
0.3%
0.06451612903 13
 
0.3%
0.02380952381 13
 
0.3%
0.1428571429 13
 
0.3%
0.025 12
 
0.3%
Other values (1219) 2649
61.2%
ValueCountFrequency (%)
0 1555
35.9%
0.005464480874 1
 
< 0.1%
0.005479452055 1
 
< 0.1%
0.005494505495 1
 
< 0.1%
0.005509641873 1
 
< 0.1%
0.005602240896 2
 
< 0.1%
0.005617977528 1
 
< 0.1%
0.005633802817 2
 
< 0.1%
0.005681818182 1
 
< 0.1%
0.005698005698 2
 
< 0.1%
ValueCountFrequency (%)
34 1
 
< 0.1%
6 1
 
< 0.1%
4 1
 
< 0.1%
2 6
0.1%
1.5 1
 
< 0.1%
1.333333333 2
 
< 0.1%
1 4
0.1%
0.6666666667 3
0.1%
0.5522788204 1
 
< 0.1%
0.5349462366 1
 
< 0.1%

avg_order_value
Real number (ℝ)

Distinct4241
Distinct (%)98.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean369.72062
Minimum-796.86
Maximum13206.5
Zeros9
Zeros (%)0.2%
Negative3
Negative (%)0.1%
Memory size67.6 KiB
2023-06-25T19:51:56.759284image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum-796.86
5-th percentile85.013125
Q1173.8975
median282.301
Q3420.7745
95-th percentile890.82462
Maximum13206.5
Range14003.36
Interquartile range (IQR)246.877

Descriptive statistics

Standard deviation465.27961
Coefficient of variation (CV)1.2584627
Kurtosis201.77649
Mean369.72062
Median Absolute Deviation (MAD)118.065
Skewness10.60863
Sum1600150.8
Variance216485.11
MonotonicityNot monotonic
2023-06-25T19:51:56.918815image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 9
 
0.2%
76.32 4
 
0.1%
120 3
 
0.1%
113.5 3
 
0.1%
35.4 3
 
0.1%
440 3
 
0.1%
326.4 2
 
< 0.1%
436.005 2
 
< 0.1%
358 2
 
< 0.1%
72 2
 
< 0.1%
Other values (4231) 4295
99.2%
ValueCountFrequency (%)
-796.86 1
 
< 0.1%
-141.48 1
 
< 0.1%
-47.965 1
 
< 0.1%
0 9
0.2%
5.684341886 × 10-141
 
< 0.1%
4.547473509 × 10-131
 
< 0.1%
3.75 1
 
< 0.1%
5.9 1
 
< 0.1%
7.5 1
 
< 0.1%
9.14 1
 
< 0.1%
ValueCountFrequency (%)
13206.5 1
< 0.1%
9338.38 1
< 0.1%
7178.633333 1
< 0.1%
6207.67 1
< 0.1%
6181.909 1
< 0.1%
4873.81 1
< 0.1%
4366.78 1
< 0.1%
4327.621667 1
< 0.1%
4314.72 1
< 0.1%
4151.26 1
< 0.1%

Interactions

2023-06-25T19:51:49.873576image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T19:51:24.549364image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T19:51:26.352479image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T19:51:28.188970image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T19:51:30.193586image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T19:51:32.194450image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T19:51:34.333731image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T19:51:36.502291image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T19:51:38.484594image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T19:51:40.361272image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T19:51:42.284173image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T19:51:44.075132image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T19:51:45.973121image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T19:51:47.898352image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T19:51:50.007796image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T19:51:24.670086image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T19:51:26.474097image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T19:51:28.319638image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T19:51:30.333688image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T19:51:32.319445image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T19:51:34.467147image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T19:51:36.630449image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T19:51:38.614009image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T19:51:40.480754image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T19:51:42.407830image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T19:51:44.199042image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T19:51:46.108663image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T19:51:48.058073image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T19:51:50.141180image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T19:51:24.794444image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T19:51:26.590575image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T19:51:28.454699image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T19:51:30.468134image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T19:51:32.443551image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T19:51:34.601145image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T19:51:36.754604image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T19:51:38.767185image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T19:51:40.600703image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T19:51:42.527589image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T19:51:44.322513image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T19:51:46.243650image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T19:51:48.241882image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T19:51:50.314775image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T19:51:24.928726image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T19:51:26.733346image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T19:51:28.586435image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T19:51:30.618426image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T19:51:32.576266image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T19:51:34.749259image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T19:51:36.916362image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T19:51:38.906755image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T19:51:40.727870image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T19:51:42.655204image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T19:51:44.457559image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T19:51:46.389266image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T19:51:48.376674image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T19:51:50.451719image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T19:51:25.060750image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T19:51:26.883126image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T19:51:28.734505image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T19:51:30.771181image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T19:51:32.727333image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T19:51:34.901747image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T19:51:37.079220image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T19:51:39.047723image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T19:51:40.863319image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T19:51:42.790247image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T19:51:44.605193image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T19:51:46.537077image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T19:51:48.519119image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T19:51:50.587060image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T19:51:25.183922image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T19:51:27.015180image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T19:51:28.889177image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T19:51:30.932467image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T19:51:32.863053image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T19:51:35.068950image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T19:51:37.229155image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T19:51:39.172337image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T19:51:41.037773image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T19:51:42.916769image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T19:51:44.743571image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T19:51:46.672901image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T19:51:48.650779image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T19:51:50.725038image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T19:51:25.316450image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T19:51:27.143570image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T19:51:29.034933image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T19:51:31.078274image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T19:51:32.997214image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T19:51:35.233741image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T19:51:37.383640image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T19:51:39.307877image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T19:51:41.189306image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T19:51:43.051586image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T19:51:44.893033image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T19:51:46.811571image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T19:51:48.790706image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T19:51:50.869868image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T19:51:25.448416image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T19:51:27.278392image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T19:51:29.171798image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T19:51:31.229439image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T19:51:33.143089image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T19:51:35.453706image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T19:51:37.519686image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T19:51:39.442721image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T19:51:41.328712image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T19:51:43.186733image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T19:51:45.038633image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T19:51:46.956376image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T19:51:48.930142image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T19:51:51.018993image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T19:51:25.568511image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T19:51:27.400457image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T19:51:29.313511image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T19:51:31.362459image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T19:51:33.313723image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T19:51:35.637612image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T19:51:37.653196image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T19:51:39.554431image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T19:51:41.482565image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T19:51:43.301783image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T19:51:45.160775image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T19:51:47.089692image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T19:51:49.050806image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T19:51:51.173219image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T19:51:25.684025image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T19:51:27.529175image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T19:51:29.450506image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T19:51:31.490936image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T19:51:33.499136image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T19:51:35.858550image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T19:51:37.797838image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T19:51:39.673012image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T19:51:41.602536image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T19:51:43.432165image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T19:51:45.284944image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T19:51:47.217743image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T19:51:49.172734image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T19:51:51.301123image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T19:51:25.811068image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T19:51:27.646346image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T19:51:29.587887image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T19:51:31.626841image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T19:51:33.679578image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T19:51:35.979687image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T19:51:37.931148image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T19:51:39.801179image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T19:51:41.725097image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T19:51:43.550732image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T19:51:45.406704image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T19:51:47.350635image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T19:51:49.290866image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T19:51:51.437166image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T19:51:25.950608image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T19:51:27.773995image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T19:51:29.736632image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T19:51:31.784158image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T19:51:33.842967image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T19:51:36.106567image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T19:51:38.065761image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T19:51:39.924490image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T19:51:41.861054image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T19:51:43.675098image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T19:51:45.542685image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T19:51:47.491212image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T19:51:49.448174image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T19:51:51.605484image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T19:51:26.090353image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T19:51:27.924212image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T19:51:29.892898image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T19:51:31.923036image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T19:51:34.051325image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T19:51:36.241154image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T19:51:38.201920image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T19:51:40.061577image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T19:51:41.990579image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T19:51:43.811546image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T19:51:45.691567image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T19:51:47.630792image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T19:51:49.604026image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T19:51:51.744504image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T19:51:26.221555image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T19:51:28.053660image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T19:51:30.047590image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T19:51:32.060401image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T19:51:34.194001image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T19:51:36.374229image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T19:51:38.351167image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T19:51:40.237210image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T19:51:42.144996image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T19:51:43.950291image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T19:51:45.835726image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T19:51:47.763152image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-25T19:51:49.741579image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Correlations

2023-06-25T19:51:57.087510image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
customer_idmonetaryunique_prodsqt_prodsavg_basket_sizerecencyrelationship_durationpurchase_countreturns_countavg_unit_pricereturn_rateavg_purchase_intervalfrequencyavg_order_value
customer_id1.000-0.078-0.009-0.006-0.0040.008-0.0090.000-0.053-0.017-0.056-0.005-0.005-0.124
monetary-0.0781.0000.7340.7880.313-0.4870.7240.8060.4560.0210.3980.6320.6320.676
unique_prods-0.0090.7341.0000.9830.744-0.4580.6020.6550.352-0.0820.3010.4990.4990.424
qt_prods-0.0060.7880.9831.0000.680-0.5000.6640.7320.386-0.0840.3280.5590.5590.423
avg_basket_size-0.0040.3130.7440.6801.000-0.1370.0620.0470.040-0.1310.0400.0120.0120.466
recency0.008-0.487-0.458-0.500-0.1371.000-0.563-0.564-0.2540.096-0.205-0.431-0.431-0.133
relationship_duration-0.0090.7240.6020.6640.062-0.5631.0000.8950.4200.0080.3590.6210.6210.145
purchase_count0.0000.8060.6550.7320.047-0.5640.8951.0000.4760.0050.4030.8050.8050.154
returns_count-0.0530.4560.3520.3860.040-0.2540.4200.4761.0000.0590.9890.3630.3630.190
avg_unit_price-0.0170.021-0.082-0.084-0.1310.0960.0080.0050.0591.0000.0630.0040.0040.031
return_rate-0.0560.3980.3010.3280.040-0.2050.3590.4030.9890.0631.0000.3100.3100.184
avg_purchase_interval-0.0050.6320.4990.5590.012-0.4310.6210.8050.3630.0040.3101.0001.0000.113
frequency-0.0050.6320.4990.5590.012-0.4310.6210.8050.3630.0040.3101.0001.0000.113
avg_order_value-0.1240.6760.4240.4230.466-0.1330.1450.1540.1900.0310.1840.1130.1131.000

Missing values

2023-06-25T19:51:51.944733image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
A simple visualization of nullity by column.
2023-06-25T19:51:52.227896image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

customer_idmonetaryunique_prodsqt_prodsavg_basket_sizerecencyrelationship_durationpurchase_countreturns_countavg_unit_pricereturn_rateavg_purchase_intervalfrequencyavg_order_value
012347.04310.0010318226.000000236570.02.6440110.00.0191780.019178615.714286
112348.01437.2421276.7500007528340.00.6929630.00.0141340.014134359.310000
212349.01457.55727272.00000018010.04.2375000.00.0000000.0000001457.550000
312350.0294.40161616.000000310010.01.5812500.00.0000000.000000294.400000
412352.01265.41577711.00000036260763.04.0754559.00.0269230.026923180.772857
512353.089.00444.000000204010.06.0750000.00.0000000.00000089.000000
612354.01079.40585858.000000232010.04.5037930.00.0000000.0000001079.400000
712355.0459.40131313.000000214010.04.2038460.00.0000000.000000459.400000
812356.02487.43525819.3333332230330.02.9460340.00.0099010.009901829.143333
912357.06207.67131131131.00000033010.03.3486260.00.0000000.0000006207.670000
customer_idmonetaryunique_prodsqt_prodsavg_basket_sizerecencyrelationship_durationpurchase_countreturns_countavg_unit_pricereturn_rateavg_purchase_intervalfrequencyavg_order_value
431818273.0204.00131.000000225530.02.5500000.00.0117650.01176568.000000
431918274.00.00111111.000000300188.03.67181888.00.0000000.0000000.000000
432018276.0323.36141414.00000043012.02.4821432.00.0000000.000000323.360000
432118277.097.63888.00000058011.03.1412501.00.0000000.00000097.630000
432218278.0173.90999.00000073010.03.2833330.00.0000000.000000173.900000
432318280.0180.60101010.000000277010.04.7650000.00.0000000.000000180.600000
432418281.080.82777.000000180010.05.6228570.00.0000000.00000080.820000
432518282.0176.6012126.000000711925.05.1991672.50.0168070.01680788.300000
432618283.02088.9326275447.1250003334160.01.6113790.00.0479040.047904130.558125
432718287.01837.28597023.3333334215930.01.4935710.00.0188680.018868612.426667